MCO Molecular and Clinical Oncology 2049-9450 2049-9469 D.A. Spandidos 10.3892/mco.2016.842 MCO-0-0-842 Articles Prognostic significance of microRNA-200c in various types of cancer: An updated meta-analysis of 34 studies ZHANGJIA-YI 1 * WANGYA-MIN 1 * SONGLE-BIN 2 * CHENCHEN 1 WANGYI-CHUN 1 SONGNING-HONG 1 Department of Urology, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, P.R. China The First Clinical Medical College of Nanjing Medical University, Nanjing 210029, P.R. China Correspondence to: Dr Ning-Hong Song, Department of Urology, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, P.R. China, E-mail: doctorurology@yeah.net

Contributed equally

 06 2016 30 03 2016 4 6 933 941 21012016 18032016 Copyright: © Zhang et al. 2016 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Previous studies have indicated that miR-200c is a promising cancer biomarker. However, different studies have presented conflicting results. Therefore, the aim of the present study was to perform a meta-analysis of miR-200c based on 34 relevant studies. The Materials and methods sections of papers were carefully identified using the databases PubMed, Web of Science and Embase for publications up to December 4, 2015. Pooled hazard ratios (HRs) and 95% confidence intervals (95% CIs) were systematically calculated to investigate the association between the expression of miR-200c and cancer prognosis. The results demonstrated that elevated expression levels of miR-200c indicated significantly worse overall survival rates (HR=1.37, 95% CI: 1.01, 1.85), and a high level of miR-200c was considered an indicator of an unfavorable prognosis in patients from Europe and America (HR=1.85, 95% CI: 1.27, 2.69). Furthermore, overexpression of miR-200c was significantly associated with progression of the disease in the subgroups of tissue and blood samples (HR=0.68 and 2.45, respectively), and inferior overall survival rates for the blood subgroup were revealed (HR=2.21, 95% CI: 1.04, 4.72). In addition, miR-200c was of prognostic value in several disease subgroups. Taken together, high expression levels of miR-200c are of significant prognostic value in various human malignancies.

 cancer miR-200c prognosis hazard ratio meta-analysis Introduction

Cancer has become the primary cause of mortality in the majority of countries and regions worldwide, and the incidence of cancer has increased substantially in recent years (1). In 2012, 14.1 million new cancer cases, 8.2 million cancer mortalities and 32.6 million individuals living with cancer (within 5 years of diagnosis) were reported worldwide. Specifically, 57% (8 million) of new cancer cases, 65% (5.3 million) of cancer mortalities and 48% (15.6 million) of the 5-year prevalent cancer cases occurred in less developed regions (2). Due to the difficulty of early diagnosis and the low survival rate of multiple cancer types, reliable biomarkers that are associated with the diagnosis or prognosis of cancer are urgently required.

MicroRNAs are conserved small non-coding RNAs with a length of ~18–25 nucleotides, which regulate the expression of target genes and exert vital roles in various biological processes (3,4). They were first identified in 1993 (5). Thereafter, an understanding of their roles in the cell cycle, apoptosis, proliferation and differentiation has greatly advanced (6,7). Furthermore, several microRNAs were identified that function as either oncogenes or tumor suppressors, and the expression levels of certain microRNAs were associated with the degree of malignancy (8–10). Due to their good stability and unique expression profiles in human malignancies, microRNAs hold great promise as conceivable biomarkers for cancer diagnosis and prognosis (11,12).

MicroRNA-200c (miR-200c), the most representative member of the microRNA-200 family, has been widely investigated during the last few years. miR-200c was revealed to exert a critical role in the regulation of epithelial-to-mesenchymal transition (EMT) and mesenchymal-to-epithelial transition (MET) (13,14). In addition, there have been numerous studies demonstrating the association between an aberrant expression level of miR-200c and the prognosis of various human malignancies, including endometrial cancer (8,9), gastric cancer (13,15–17), ovarian cancer (18–21), clear cell renal cell carcinoma (ccRCC) (22–24), breast cancer (25–28), colorectal cancer (14,29), non-small cell lung cancer (NSCLC) (30–35), prostate cancer (36), esophageal cancer (37–39), diffuse large B-cell lymphoma (40), bladder cancer (41,42) and pancreatic cancer (43). Approximately half of these studies verified the anti-oncogenic function of miR-200c in certain cancer types, indicating the potential correlation of elevated expression levels of miR-200c and superior prognosis (13–15,18,20–22,28,29,31,35,41–43). However, other studies have provided opposing evidence, suggesting that miR-200c serves as an oncogene (23–27,36–39). Therefore, miR-200c is a noteworthy biomarker for cancer prognosis, and a meta-analysis of its precise role is required. To clarify the value of miR-200c as a prognostic biomarker, data from studies of miR-200c in various cancer types were systematically collected and evaluated.

 Materials and methods <sec> <title>Search strategy

Relevant studies were identified by carefully searching the online databases PubMed, Web of Science and Embase up to December 4th, 2015. The following combination of keywords was simultaneously applied for the literature search: ‘microRNA-200c’ or ‘microrna-200c’ or ‘miRNA-200c’ or ‘miR-200c’ and ‘tumor’ or ‘cancer’ or ‘carcinoma’ or ‘neoplasm’ or ‘malignancies’. In addition, the following criteria for the study characteristics were used to improve the search further: i) English language publications; ii) studies that concentrated on patients with malignancies; and iii) studies that demonstrated the association of miR-200c expression with cancer prognosis. This comprehensive online search was independently performed by two authors (Jia-Yi Zhang and Ya-Min Wang).

 Inclusion and exclusion criteria

The present meta-analysis was performed strictly following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (44). Articles were considered eligible if they met the following criteria: i) the expression level of miR-200c had been assessed in tissue or peripheral blood samples from cancer patients; ii) dichotomous categorization of expression levels of miR-200c had been investigated according to a cut-off value; and iii) an investigation had been made of the association of expression levels of miR-200c with survival rates or recurrence, together with a corresponding hazard ratio (HR) or survival curve. If more than one article had been published on the identical study cohort, only the most comprehensive study was selected for the present meta-analysis. In addition, letters, review articles and experiments on animals were excluded. A flow diagram of the study selection process with further details is shown in Fig. 1.

 Data extraction

All eligible studies were identified by Ya-Min Wang and Le-Bin Song, and uncertain data were reassessed by Ning-Hong Song. The data extraction included the following elements: i) the first author and publication year; ii) characteristics of the studied population, including patient nationality, number, mean or median age, disease type and stage, and sample examined; iii) study design, assay method and cut-off definition; iv) HRs of elevated expression levels of miR-200c for cancer-specific survival (CSS), overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS) and disease-free survival (DFS); and v) mean or median follow-up duration. If HRs were not directly reported in the studies, then the data were extracted from Kaplan-Meier survival plots using Engauge Digitizer v.5.1 (license type: GPL; developed by Mark Mitch; Category: C:Science/CAD) to calculate HRs with 95% confidence intervals (95% CIs) using methods that are previously described (45). Furthermore, if both the univariate and multivariate results were reported, then only the latter was selected, since these results were adjusted for confounding factors. All the above-mentioned data are comprehensively shown in Tables I and II.

 Statistical analysis

In the present meta-analysis, HRs and corresponding 95% CIs were combined to estimate the value of high expression levels of miR-200c for cancer prognosis. An individual or pooled HR of >1.0 indicated poorer prognosis in patients with miR-200c overexpression, and an HR of <1.0 represented an improved prognosis. Furthermore, a fixed-effects model using the Mantel-Haenszel method or a random-effects model using the DerSimonian-Laird method was applied for the meta-analysis, according to the heterogeneity between the pooled studies (46). Statistical heterogeneity was evaluated by performing the Chi-square test (assessing the P-value) and by calculating the Higgins I2 statistic. If significant heterogeneity was observed (P<0.10 or I2>50%), the random-effects model was applied; otherwise, the fixed-effects model was used. Subgroup analyses were further performed to investigate the source of the identified heterogeneity. In addition, sensitivity analyses were implemented to avoid biases in the results due to certain low-quality studies, and the publication bias was estimated using Begg's and Egger's tests. All P-values were two-sided, and P<0.05 was considered to indicate a statistically significant value. All statistical analyses were conducted using Stata v.12.0 (StataCorp, College Station, Texas, USA), and Microsoft Excel (v.2010, Microsoft Corporation, Redmond, Washington, USA).

 Results <sec> <title>Summary of the included studies

In total, 987 articles were initially collected from a primary retrieval using the databases PubMed, Web of Science and Embase. Of these articles, 33 articles that included 34 studies [the article of Marchini et al (20) included independent studies of two different cohorts, tissue collections A and B (20)] were ultimately considered eligible by screening the titles, abstracts and full texts (Fig. 1). Of these studies of the association between expression levels of miR-200c and the survival rate or disease recurrence in human malignancies, 27 were retrospective, and seven were prospective. In total, 3,940 patients from China, Germany, Finland, Japan, Spain, Australia, South Korea, Belgium, Sweden, Poland, USA, Italy or Denmark were included; these patients were diagnosed with a variety of cancer types, including endometrial cancer (8,9), gastric cancer (13,15–17), ovarian cancer (18–21), ccRCC (22–24), breast cancer (25–28), colorectal cancer (14,29), NSCLC (30–35), prostate cancer (36), esophageal cancer (37–39), diffuse large B-cell lymphoma (40), bladder cancer (41,42) and pancreatic cancer (43). Tissue samples were predominantly used to determine expression levels of miR-200c, although six studies detected expression levels of miR-200c in serum or plasma, and one study used tissue and blood samples (14). To assess miRNA-200c expression, quantitative real-time polymerase chain reaction (RT-qPCR) had predominantly been used in 32 studies, and in situ hybridization (ISH) was performed in three studies. The characteristics of primary studies are systematically summarized in Table I.

 Association of CSS/OS with miR-200c overexpression

In total, 26 studies were included in the meta-analysis of the association between miR-200c overexpression and CSS/OS, and a random-effects model was applied due to the high level of heterogeneity (P<0.001, I2=86.2%). Three studies were excluded, since they enrolled cancer patients of only stage I (20,42). The pooled value of HRs from individual studies was 1.37 (95% CI: 1.01, 1.85), along with a P-value of 0.040 (Fig. 2A). Therefore, this result indicated a significant correlation of CSS/OS with high expression levels of miR-200c.

Furthermore, subgroup analyses were performed on specific study characteristics, including region, disease type and sample detection. All the pooled HRs with 95% CIs of the subgroups are shown in Fig. 2B and C. First, in the subgroup analysis of patients from Europe and America, the pooled outcome demonstrated that a high expression level of miR-200c was significantly associated with worse OS (HR=1.85, 95% CI: 1.27, 2.69). Secondly, the subgroups of esophageal cancer and endometrial cancer exhibited an identical association, with HR values of 1.68 and 2.18, respectively. However, the colorectal cancer subgroup demonstrated the opposite result (HR=0.54, 95% CI: 0.32, 0.90). Thirdly, the result for the blood sample subgroup significantly revealed that miR-200c overexpression was associated with worse OS, with an HR value of 2.21 (95% CI: 1.04–4.72). No significant results were identified in the other subgroups.

 Association of disease progress with miR-200c overexpression

A total of 16 studies were included in the present meta-analysis of the association of miR-200c overexpression and RFS/PFS/DFS; the random-effects model was used due to the high level of heterogeneity (P<0.001, I2=87.1%). Two studies from the literature were excluded, since they enrolled cancer patients at only stage I (20). The pooled HR from individual studies was 1.03, along with a P-value of 0.880, indicating a lack of statistical significance (Fig. 3A). Therefore, subgroup analyses were performed to reduce the confounding influence of the apparent heterogeneity (Fig. 3B).

First, high expression levels of miR-200c were shown to correlate significantly with improved disease progression in patients with NSCLC (HR=0.48, 95% CI: 0.34, 0.68; fixed-effects model: P=0.235, I2=29.2% for the heterogeneity test). Secondly, the pooled HR of the tissue subgroup was 0.68 (95% CI: 0.48, 0.96, random-effects model; P<0.001, I2=82.3% for the heterogeneity test), suggesting an association between miR-200c overexpression and favorable patient prognosis. However, the blood subgroup revealed a significant correlation of expression levels of miR-200c with unfavorable patient prognosis (HR=2.45, 95% CI: 1.85, 3.26; fixed-effects model: P=0.722, I2=0.0% for heterogeneity test).

 Sensitivity analysis

In the studies of CSS/OS and RFS/PFS/DFS, our sensitivity analyses did not reveal any alterations in the results due to the inclusion of any individual study (Fig. 4A and B), indicating that no single study significantly influenced the pooled HRs and 95% CIs.

 Publication bias

Egger's test and Begg's funnel plot were used for the analysis of publication bias. The funnel plots of the CSS/OS and RFS/PFS/DFS analyses were almost symmetrical, and all P-values from the Egger's test were >0.05 (Fig. 4C and D). Therefore, no significant publication bias was observed in the present meta-analysis.

 Discussion

The EMT is a well-established mechanism that includes intercellular contact disruption and enhanced cell motility (47). Additionally, a burgeoning body of evidence has clearly demonstrated the involvement of EMT in the invasion and migration of tumor cells (14,32,43). Intracellular and extracellular factors are known to be capable of promoting or inhibiting EMT progression. In particular, the miR-200 family has been proposed to suppress EMT by directly targeting the transcriptional repressors of E-cadherin, zinc finger E-box binding homeobox 1 (ZEB1) and zinc finger E-box binding homeobox 2 (ZEB2), thus inducing E-cadherin upregulation (48). Conversely, inhibition of the miR-200 family would induce mesenchymal-like spindle morphology, which promotes cancer metastasis.

As the most representative microRNA among the miR-200 family, miR-200c fulfills important roles in EMT inhibition and in MET promotion. For instance, Marchini et al (20) demonstrated that several downstream targets of miR-200c, including vascular endothelial growth factor A (VEGFA) and tubulin, beta 3 class III (TUBB3), were significantly upregulated in patients with ovarian cancer who relapsed (20). Leskelä et al (21) suggested an inverse correlation between miR-200c and TUBB3 expression in advanced ovarian cancer. Furthermore, a marked inverse correlation of the expression levels of miR-200c and the mRNA levels of VEGFA was demonstrated in two independent cohorts of ccRCC and normal tissues (49). Thus, miR-200c has been considered a tumor suppressor.

However, a potential oncogenic role of miR-200c in human malignancies has also been reported. Tuomarila et al (25) demonstrated that progesterone receptor (PR)-negative cases with local or distant recurrence had higher expression levels of miR-200c compared with those without recurrence, suggesting that a high expression level of miR-200c is an independent factor for predicting poor survival rates in PR-negative breast cancer. Tejero et al (30) reported that high expression levels of miR-200c were associated with shorter OS of patients with NSCLC due to MET and angiogenesis (30). In addition, Hamano et al (39) indicated that the miR-200c-induced chemoresistance of esophageal cancer was mediated by the Akt pathway, showing that miR-200c overexpression was significantly correlated with a shortened OS (39).

In the present meta-analysis, a significant association of the expression of miR-200c with outcome was observed for pooled CSS/OS (Fig. 2A). However, there was heterogeneity in both groups of outcomes (P<0.001, I2=86.2% for CSS/OS; P<0.001, I2=87.1% for RFS/PFS/DFS). Heterogeneity may be caused by the different characteristics of the patients, including race, disease type and clinical stage, as well as the selected cut-off value of the expression level of miR-200c. To minimize the influence of these confounding factors, subgroup analyses that focused on region, disease type and sample detection were performed. On the basis of the subgroup analyses of the included studies, heterogeneity in several subgroups was greatly reduced, and valuable results were obtained (Fig. 2B and C). These results indicate that miR-200c may be used as a prognostic biomarker; however, several details require further refinement. First, different cut-off values were used in the studies of miR-200c. The majority of the available studies established a median or mean expression cut-off value, although certain studies used a lower quartile value. Furthermore, several studies used a ternary method, separating the expression levels of miR-200c into high, intermediate and low categories (50). Due to the lack of standardized miR-200c expression data, evaluating its prognostic role in malignancies would produce inaccurate results. Secondly, whether miR-200c functions as an independent tumor biomarker or, more likely, as a component of a predictive microRNA signature, has yet to be firmly established. For instance, Yeh et al (51) demonstrated that the downregulation of miR-141 and miR-200c serves as an independent predictor of DFS in hepatocellular carcinoma. In the multivariate analysis performed by Blanco-Calvo et al (52), the combination of high levels of growth differentiation factor 15, matrix metalloproteinase 7 and miR-200c was considered an independent predictor of mortality in gastric cancer. In addition, using a linear combination of the microRNA cycle threshold values and Cox regression coefficients as weights, Berghmans et al (33) revealed that a certain microRNA signature (miR-200c, miR-124, miR-29c and miR-424) is of prognostic value for OS in patients with NSCLC (33). Thirdly, although significant results were identified for several subgroups based on the subgroup analyses, the results for other subgroups were not decisive. Empirically, a prognostic factor is considered decisive when the HR is >2.0 or < 0.5 (53). Finally, several HRs were extracted from the survival curves, which unavoidably resulted in several slight statistical errors.

In conclusion, we have demonstrated that high expression levels of miR-200c are of significant prognostic value in various human malignancies. In addition, expression levels of miR-200c in tumor tissue and blood samples were considered to serve as a reliable predictive biomarker for disease progression in cancer patients. Due to the complex role of miR-200c in tumor progression and metastasis, further investigations at a larger scale are required to establish the usefulness of miR-200c as a prognostic biomarker.

 Acknowledgements

We would like to thank the authors of the primary studies.

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Flow diagram with details of the study selection process.

Forest plots of the combined analyses of the association of CSS/OS and expression levels of miR-200c. (A) Forest plots of the pooled analysis of CSS/OS. Squares and horizontal lines correspond to study-specific HRs and 95% CIs, respectively. The area of the squares correlates with the weight, and the diamonds represent the pooled HRs and 95% CIs. (B) Forest plots of the pooled analysis of CSS/OS in different disease type subgroups. (C) Forest plots of the pooled analysis of CSS/OS in blood sample subgroup. CSS, cancer-specific survival; OS, overall survival; HR, hazard ratio; CI, confidence interval.

Forest plots. (A) Forest plots of the pooled analysis of the association of RFS/PFS/DFS and miR-200c expression in different sample subgroups. (B) Forest plots of the pooled analysis of RFS/PFS/DFS in the in the non-small cell lung cancer subgroup. RFS, recurrence-free survival; PFS, progression-free survival; DFS, disease-free survival; HR, hazard ratio; CI, confidence interval.

Sensitivity analyses and Begg's funnel plots. (A) Sensitivity analysis of the effect of individual studies on the CSS/OS results. (B) Sensitivity analysis of the effect of individual studies on the RFS/PFS/DFS results. (C) Begg's funnel plots to test for the publication bias in the overall analysis of CSS/OS. Each point represents a separate study. (D) Begg's funnel plots to test for publication bias in the overall analysis of RFS/PFS/DFS. RFS, recurrence-free survival; PFS, progression-free survival; DFS, disease-free survival; HR, hazard ratio; CI, confidence interval.

The predominant characteristics of the included studies.

Authors, year Patient's nationality Patient's number Mean or median age Study design Malignant disease Disease stage Detected sample Mean or median follow-up time Refs.
Antolín et al, 2015 Spain 57 55.4 R Breast cancer I–IV Blood 264.6OS/235.3PFS weeks (27)
Butz et al, 2015 Canada 425 NM R ccRCC I–IV Tissue NM (24)
Song et al, 2015 China 134 50.0 R Breast cancer I–IV Tissue NM (28)
Zhao et al, 2015 China 78 61.4 P NSCLC IIB-IIIB Tissue NM (35)
Zhou et al, 2015 China 63 65.0 R Gastric cancer IIB-IV Tissue NM (13)
Gao et al, 2015 China 93 NM R Ovarian cancer I–IV Blood NM (18)
Vergho et al, 2014 Germany 37 66.8 R ccRCC I–IV Tissue 45.6 months (22)
Tuomarila et al, 2014 Finland 172 60.4 P Breast cancer I–IV Tissue 9.7 years (25)
Toiyama et al, 2014 Japan 156T/182S 68.0 R Colorectal cancer I–IV Both 20 months (14)
Tejero et al, 2014 Spain 155 65.0 R NSCLC I–III Tissue 43 months (30)
Song et al, 2014 China 373 60.5 R Gastric cancer I–IV Tissue 35 months (17)
Lin et al, 2014 Australia 97 68.0 P Prostate cancer III–IV Blood 12 months (36)
Li et al, 2014 China 150 59.0 R NSCLC IIIB, IV Tissue 16.7 months (31)
Kim et al, 2014 South Korea 72 64.0 R NSCLC I–IV Tissue 31 months (32)
Diaz et al, 2014 Spain 127 67.4 R Colorectal cancer I–III Tissue 113 months (29)
Cao et al, 2014 China 100 58.0 R Ovarian cancer I–IV Tissue 36.8 months (19)
Berghmans et al, 2013 Belgium 38 59.0 P NSCLC NM Tissue NM (33)
Yu et al, 2013 China 157 60.0 R Esophageal cancer III, IV Blood 20 months (37)
Wotschofsky et al, 2013 Germany 111 >60.0 R ccRCC NM Tissue NM (23)
Tang et al, 2013 China 167 60.0 R Gastric cancer I–IV Tissue NM (15)
Tanaka et al, 2013 Japan 64 67.5 R Esophageal cancer II–IV Blood NM (38)
Berglund et al, 2013 Sweden 61 >60.0 R DLBCL I–IV Tissue NM (40)
Madhavan et al, 2012 Germany 193 NM R Breast cancer III–IV Blood NM (26)
Valladares-Ayerbes et al, 2012 Spain 52 65.3 P Gastric cancer I–IV Blood 24 months (16)
Torres et al, 2013 Poland 108 62.8 P Endometrial cancer I–IV Tissue NM (9)
Liu et al, 2012 China 70 60.0 P NSCLC I–IV Tissue NM (34)
Karaayvaz et al, 2012 USA 34 NM R Endometrial cancer I–IV Tissue NM (8)
Wszolek et al, 2011 USA 57 >60.0 R Bladder cancer NM Tissue 92 months (41)
Marchini et al, 2011 Italy 89 52.0 R Ovarian cancer I Tissue 110 months (20)
Marchini et al, 2011 Italy 55 57.0 R Ovarian cancer I Tissue 108 months (20)
Hamano et al, 2011 Japan 98 >60.0 R Esophageal cancer I–IV Tissue 28.8 months (39)
Wiklund et al, 2011 Denmark 100 NM R Bladder cancer I Tissue NM (42)
Yu et al, 2010 Japan 99 65.7 R Pancreatic cancer I–IV Tissue NM (43)
Leskelä et al, 2010 Spain 72 57.0 R Ovarian cancer I–IV Tissue NM (21)

The study design is described as prospective (P) or retrospective (R) T, tissue sample of patients was assayed; S, serum sample of patients was assayed; ccRCC, clear cell renal cell carcinoma; NSCLC, non-small cell lung cancer; DLBCL, diffuse large B-cell lymphoma; NM, not mentioned; OS, overall survival; PFS, progression-free survival.

HRs of included studies.

HRs
Authors, year Main assay of miR200c Cut-off Resource of HR OS/CSS RFS/PFS/DFS Refs.
Antolín et al, 2015 RT-qPCR Mean Reported 2.79 3.33 (27)
Butz et al, 2015 RT-qPCR Mean Reported 2.73 3.57 (24)
Song et al, 2015 ISH Mean a 0.18 0.19 (28)
Zhao et al, 2015 RT-qPCR Median Reported – 0.35 (35)
Zhou et al, 2015 RT-qPCR Median a – 0.49 (13)
Gao et al, 2015 RT-qPCR Mean Reported 0.32 – (18)
Vergho et al, 2014 RT-qPCR 2.73 Reported 0.95 – (22)
Tuomarila et al, 2014 RT-qPCR Median a 2.78 3.16 (25)
Toiyama et al, 2014 RT-qPCR Median Reported 0.56T/2.67S 4.51S (14)
Tejero et al, 2014 RT-qPCR Mean a 1.95 – (30)
Song et al, 2014 RT-qPCR Lowest quartile Reported 1.32 1.06 (17)
Lin et al, 2014 RT-qPCR Median Reported 2.30 – (36)
Li et al, 2014 RT-qPCR 0.01385 Reported 0.57 0.55 (31)
Kim et al, 2014 RT-qPCR Mean Reported 3.67 – (32)
Diaz et al, 2014 RT-qPCR NM a 0.51 0.55 (29)
Cao et al, 2014 RT-qPCR 3.84 Reported 16.22 – (19)
Berghmans et al, 2013 RT-qPCR Median Reported 1.51 – (33)
Yu et al, 2013 RT-qPCR Median Reported 1.67 – (37)
Wotschofsky et al, 2013 RT-qPCR Median Reported – 1.40 (23)
Tang et al, 2013 RT-qPCR/ISH Mean Reported 0.40 0.51 (15)
Tanaka et al, 2013 RT-qPCR Median Reported – 2.79 (38)
Berglund et al, 2013 RT-qPCR Mean a 2.68 – (40)
Madhavan et al, 2012 RT-qPCR Lower quartile a 15.27 2.20 (26)
Valladares-Ayerbes et al, 2012 RT-qPCR 62.4 Reported 2.24 2.27 (16)
Torres et al, 2013 RT-qPCR Median Reported 2.72 – (9)
Liu et al, 2012 RT-qPCR 2.00 Reported 6.02 – (34)
Karaayvaz et al, 2012 RT-qPCR 35.5 a 1.28 – (8)
Wszolek et al, 2011 RT-qPCR Mean a 0.09 – (41)
Marchini et al, 2011 RT-qPCR Median Reported 0.24 0.42 (20)
Marchini et al, 2011 RT-qPCR Median Reported 0.09 0.04 (20)
Hamano et al, 2011 RT-qPCR Median a 1.71 – (39)
Wiklund et al, 2011 ISH NM a 0.52 – (42)
Yu et al, 2010 RT-qPCR 0.64 Reported 0.45 – (43)
Leskelä et al, 2010 RT-qPCR Median Reported – 0.85 (21)

The study design is described as prospective (P) or retrospective (R).

Data extracted from the survival curve. In the OS/CSS and RFS/PFS/DFS columns, ‘T’ denotes the HR of miR-200c overexpression in tumor tissue, and ‘S’ denotes the HR of miR-200c overexpression in serum sample; HR, hazard ratio; OS, overall survival; CSS, cancer specific survival; RFS, relapse-free survival; PFS, progression-free survival; DFS, disease-free survival; RT-qPCR, quantitative reverse transcription-polymerase chain reaction; ISH, in situ hybridization.